Toward the Accurate Coverage of Aspheric Surfaces Using Two-Dimensional Scanning Paths for Minimizing Regular Errors

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Abstract:

This paper describes a two-dimensional tool-path planning model for minimizing the regularly distributed errors or mid-frequency errors during computer controlled optical surfacing (CCOS) by optimally connecting different tool-path segments. The model was established based on a neuro-fuzzy algorithm, a path neighborhood function which is defined as a victorious output element calculated in a self-organization way, then, the optimum material removal function with a modified weight was derived. The material removal function was studied theoretically and the results of simulation present a Gaussian distribution feature. Discrete removal points and optimized tool-path grid were simulated. Finally, an experiment involving a parabolic mirror was performed for residual error removal and the two-dimensional tool-path planning algorithm was found to be valid.

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Key Engineering Materials (Volumes 364-366)

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64-68

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December 2007

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© 2008 Trans Tech Publications Ltd. All Rights Reserved

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[1] R.B. Johnson: Optical Engineering Vol. 27(1) (1988), p.1046.

Google Scholar

[2] R. A. Jones and W.J. Rupp: Optical Engineering Vol. 30(1) (1991), p. (1962).

Google Scholar

[3] G. Doughty and J. Smith: Applied Optics Vol. 26(2)(1987), p.2421.

Google Scholar

[4] M. Negishi M: International Journal of the Japan Society for Precision Engineering Vol. 29(1) (1995), p.1.

Google Scholar

[5] R. A. Jones: Optical Engineering Vol. 25(6) (1986), p.785.

Google Scholar

[6] S.D. Jacobs, D. Golini, Y. Hsu, B. E. Puchebner, D. Strafford, W. I. Kordonsky, I. V. Prokhorov, E. Fess, D. Pietrowski and V. W. Kordonski: Proceedings of SPIE Vol. 2576(1995), p.372.

DOI: 10.1117/12.215617

Google Scholar

[7] R. E. Wagner and R. R. Shannon: Applied Optics Vol. 13(7) (1974), p.1683.

Google Scholar

[8] A. S. Savel'ev and A. P. Bogdanov: Soviet Journal of Optical Technology Vol. 52(5) (1985), p.294.

Google Scholar

[9] F. W. Preston: J. Soc. Glass Technology Vol. 11(1927), p.124.

Google Scholar

[10] Jyh-Shing Roger Jang, Chuen-Tai Sun and Eiji Mizutani: Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence (NJ: Prenhall Hall, 1997).

Google Scholar

[11] H. B. Cheng, Z. J. Feng and K. Cheng: International Journal of Machine Tools & Manufacture Vol. 45(9) (2005), p.1085.

Google Scholar